3 papers
cs.AI2026
Differentiable Power-Flow Optimization
Muhammed Ãz, Jasmin Hörter, Kaleb Phipps +3
With the rise of renewable energy sources and their high variability in generation, the management of power grids becomes increasingly complex and computationally demanding. Conven…
cs.LG2025
Decision-Focused Fine-Tuning of Time Series Foundation Models for Dispatchable Feeder Optimization
Maximilian Beichter, Nils Friederich, Janik Pinter +7
Time series foundation models provide a universal solution for generating forecasts to support optimization problems in energy systems. Those foundation models are typically traine…
cs.LG2024
AutoPQ: Automating Quantile estimation from Point forecasts in the context of sustainability
Stefan Meisenbacher, Kaleb Phipps, Oskar Taubert +4
Optimizing smart grid operations relies on critical decision-making informed by uncertainty quantification, making probabilistic forecasting a vital tool. Designing such forecastin…